Virtual Sorting Has a Distinctive Advantage in Identification of Anticorrelated Genes and Further Negative Regulators of Immune Cell Subpopulations

Abstract

Immune cells are highly plastic in both gene expression and cell phenotype. We have established a method of gene expressional plasticity and virtual sorting to evaluate immune cell subpopulations and their characteristic genes in human CD4 T cells. In this study, we continued to investigate the informatics mechanism on the effectiveness of virtual sorting. We found that virtual sorting had an overall positive correlation to the Pearson correlation in the identification of positively correlated genes. However, owing to nonlinear biological anticorrelation, virtual sorting showed a distinctive advantage for anticorrelated genes, suggesting an important role in the identification of negative regulators. In addition, based on virtual sorting results, we identified two basic gene sets among highly plastic genes, i.e., highly plastic cell cycle-associated molecules and highly plastic immune and defense response-associated molecules. Genes within each set tended to be positively connected, but genes between two sets were often anticorrelated. Further analysis revealed preferential transcription factor binding motifs existed between highly plastic cell cycle-associated molecules and highly plastic immune and defense response-associated molecules. Our results strongly suggested predetermined regulation, which was called an immune cell internal phenotype, should exist and could be mined by virtual sorting analysis. This provided efficient functional clues to study immune cell phenotypes and their regulation. Moreover, the current substantial virtual sorting results in both CD4 T cells and B cells provide a useful resource for big-data-driven experimental studies and knowledge discoveries.

A theoretical framework of immune cell phenotypic classification and discovery

“…Microarray datasets from the Affymetrix Human Genome U133 Plus 2.0 Array were directly from our previous reports (20)(21)(22) and updated to incorporate the latest samples. The raw data were downloaded from the Gene Expression Omnibus (GEO, https:// www.ncbi.nlm.nih.gov/geo/) (23) and uniformly processed as described previously (20,24).…”

“…, where P indicates the percentile rank score and n is the number of samples. According to the distribution of rank scores, the interquartile range (IQR) was defined as the difference between the 1st quartile (25th percentile, 1st Qu, Q1) and 3rd quartile (75th percentile, 3rd Qu, Q3) of expressional percentile rank scores and used to measure gene plasticity as the GPL score (IQR method) (20)(21)(22), that is, GPL score (iqr) = IQR = Q3 -Q1. In this study, however, the absolute GPL score was also used to measure gene plasticity.…”

“…Virtual sorting (or in silico sorting) means analyzing a large number of data samples in a virtual way because there are no actual immune cells sorted as done in the FACS process (21,22). It was used to select cell samples according to gene expression intensity, which was similar to the gating process in flow cytometry, to perform a series of analyses (20)(21)(22).…”

“…The current model explains the infinite diversity of immune cells. Through correlated and anticorrelated gene analysis via virtual sorting (21,22), the acquired (or cophenotypes) and lost (or mutually exclusive phenotypes) phenotypes related to highly plastic genes were also analyzed. The single-cell transcriptome supported the reliability of the results.…”

ImmuMethy, a database of DNA methylation plasticity at a single cytosine resolution in human blood and immune cells

“…In our previous studies, we performed the quantitative measurement of gene plasticity, which was referred to as expressional gene plasticity ( 51 ), and potential applications based on plasticity analysis were implicated, such as marker gene evaluation ( 51 ), novel immune cell subpopulation identification ( 52 ) and internal phenotype analysis according to the correlated and anticorrelated expressional relationships ( 53 ). The current study focuses on gene plasticity at the DNA methylation level, i.e.…”